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Publication Abstract from PubMed

The design of completely synthetic proteins from first principles-de novo protein design-is challenging. This is because, despite recent advances in computational protein-structure prediction and design, we do not understand fully the sequence-to-structure relationships for protein folding, assembly, and stabilization. Antiparallel 4-helix bundles are amongst the most studied scaffolds for de novo protein design. We set out to re-examine this target, and to determine clear sequence-to-structure relationships, or design rules, for the structure. Our aim was to determine a common and robust sequence background for designing multiple de novo 4-helix bundles. In turn, this could be used in chemical and synthetic biology to direct protein-protein interactions and as scaffolds for functional protein design. Our approach starts by analyzing known antiparallel 4-helix coiled-coil structures to deduce design rules. In terms of the heptad repeat, abcdefg -i.e., the sequence signature of many helical bundles-the key features that we identify are: a = Leu, d = Ile, e = Ala, g = Gln, and the use of complementary charged residues at b and c. Next, we implement these rules in the rational design of synthetic peptides to form antiparallel homo- and heterotetramers. Finally, we use the sequence of the homotetramer to derive in one step a single-chain 4-helix-bundle protein for recombinant production in E. coli. All of the assembled designs are confirmed in aqueous solution using biophysical methods, and ultimately by determining high-resolution X-ray crystal structures. Our route from peptides to proteins provides an understanding of the role of each residue in each design.

From peptides to proteins: coiled-coil tetramers to single-chain 4-helix bundles.,Naudin EA, Albanese KI, Smith AJ, Mylemans B, Baker EG, Weiner OD, Andrews DM, Tigue N, Savery NJ, Woolfson DN Chem Sci. 2022 Sep 20;13(38):11330-11340. doi: 10.1039/d2sc04479j. eCollection , 2022 Oct 5. PMID:36320580^[1]

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.